{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training a Document Denoiser Model with AutoEncoders\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "import keras\n",
    "import cv2\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import os\n",
    "import ntpath\n",
    "from glob import glob\n",
    "from matplotlib.pyplot import imshow\n",
    "from sklearn.model_selection import train_test_split\n",
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "from keras.models import Sequential, Model, load_model\n",
    "from keras.layers import Activation, Flatten, Dropout, SpatialDropout2D, Conv2D, UpSampling2D, MaxPooling2D, add, concatenate, Input, BatchNormalization\n",
    "from keras.backend import set_image_data_format\n",
    "from keras.utils import plot_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download Dataset\n",
    "\n",
    "Download the dataset from [kaggle (denoising dirty documents)](https://www.kaggle.com/c/denoising-dirty-documents/data). You will need to be logged in to be able to download the data.\n",
    "\n",
    "Once downloaded run the following commands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!unzip denoising-dirty-documents.zip && rm denoising-dirty-documents.zip\n",
    "!mv denoising-dirty-documents/*.zip . && rm -rf denoising-dirty-documents\n",
    "!unzip '*.zip' > /dev/null && rm *.zip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the Data Generator\n",
    "\n",
    "Include data augmentation because the dataset is rather small."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_dirty = sorted(glob(\"train/*.png\"))\n",
    "x_cleaned = sorted(glob(\"train_cleaned/*.png\"))\n",
    "x_test = sorted(glob(\"test/*.png\"))\n",
    "input_shape = (260, 540)\n",
    "height = input_shape[0]\n",
    "width = input_shape[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_valid, y_train, y_valid = train_test_split(x_dirty, x_cleaned, test_size=0.20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "set_image_data_format(\"channels_last\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_train_generator(x_train, y_train, epochs, batch_size, resize_shape):\n",
    "    white_fill = 1.0\n",
    "    datagen = ImageDataGenerator(\n",
    "        rotation_range=180,\n",
    "        width_shift_range=0.2,\n",
    "        height_shift_range=0.2,\n",
    "        zoom_range=0.3,\n",
    "        fill_mode=\"constant\",\n",
    "        cval=white_fill,\n",
    "        horizontal_flip=True,\n",
    "        vertical_flip=True,\n",
    "    )\n",
    "    \n",
    "    for _ in range(epochs):\n",
    "        for x_file, y_file in zip(x_train, y_train):\n",
    "            x_img = cv2.imread(x_file, cv2.IMREAD_GRAYSCALE) / 255.0\n",
    "            y_img = cv2.imread(y_file, cv2.IMREAD_GRAYSCALE) / 255.0\n",
    "            \n",
    "            xs = []\n",
    "            ys = []\n",
    "            for i in range(batch_size):\n",
    "                if i == 0:\n",
    "                    x = x_img\n",
    "                    y = y_img\n",
    "                else:\n",
    "                    params = datagen.get_random_transform(img_shape=x_img.shape)\n",
    "                    x = datagen.apply_transform(np.expand_dims(x_img, 2), params)\n",
    "                    y = datagen.apply_transform(np.expand_dims(y_img, 2), params)\n",
    "                x = cv2.resize(x, resize_shape[::-1], interpolation=cv2.INTER_AREA)\n",
    "                y = cv2.resize(y, resize_shape[::-1], interpolation=cv2.INTER_AREA)\n",
    "                x = np.expand_dims(x, 2)\n",
    "                y = np.expand_dims(y, 2)\n",
    "                xs.append(x)\n",
    "                ys.append(y)\n",
    "            xs_imgs = np.array(xs)\n",
    "            ys_imgs = np.array(ys)\n",
    "            yield (xs_imgs, ys_imgs)\n",
    "\n",
    "def model_valid_generator(x_valid, y_valid, epochs, resize_shape):\n",
    "    xs = []\n",
    "    ys = []\n",
    "    for x_file, y_file in zip(x_valid, y_valid):\n",
    "        x_img = cv2.imread(x_file, cv2.IMREAD_GRAYSCALE) / 255.0\n",
    "        y_img = cv2.imread(y_file, cv2.IMREAD_GRAYSCALE) / 255.0\n",
    "        x = cv2.resize(x_img, resize_shape[::-1], interpolation=cv2.INTER_AREA)\n",
    "        y = cv2.resize(y_img, resize_shape[::-1], interpolation=cv2.INTER_AREA)\n",
    "        x = np.expand_dims(x, 2)\n",
    "        x = np.expand_dims(x, 0)\n",
    "        y = np.expand_dims(y, 2)\n",
    "        y = np.expand_dims(y, 0)\n",
    "        xs.append(x)\n",
    "        ys.append(y)\n",
    "    \n",
    "    for _ in range(epochs):\n",
    "        for xs_img, ys_img in zip(xs, ys):\n",
    "            yield (xs_img, ys_img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_encoder(input_shape):\n",
    "    inp = Input(shape=input_shape)\n",
    "    x = Conv2D(filters=64, kernel_size=(3,3), strides=(1,1), \n",
    "                     input_shape=input_shape, activation=\"relu\", padding=\"same\")(inp)\n",
    "    x = BatchNormalization()(x)\n",
    "    x = MaxPooling2D(pool_size=(2,2))(x)\n",
    "    \n",
    "    x = Conv2D(filters=32, kernel_size=(3,3), strides=(1,1), \n",
    "                     activation=\"relu\", padding=\"same\")(x)\n",
    "    x = BatchNormalization()(x)\n",
    "\n",
    "    return inp, x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_decoder(inp):\n",
    "    x = Conv2D(filters=32, kernel_size=(3,3), strides=(1,1), activation=\"relu\",\n",
    "                    padding=\"same\")(inp)\n",
    "    x = BatchNormalization()(x)\n",
    "    x = UpSampling2D(size=(2,2))(x)\n",
    "    \n",
    "    x = Conv2D(filters=64, kernel_size=(3,3), strides=(1,1), \n",
    "                     activation=\"relu\", padding=\"same\")(x)\n",
    "    x = BatchNormalization()(x)\n",
    "    \n",
    "    x = Conv2D(filters=1, kernel_size=(1,1), strides=(1,1), \n",
    "                     activation=\"sigmoid\", padding=\"same\")(x)\n",
    "    x = BatchNormalization()(x)\n",
    "    \n",
    "    return inp, x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_autoencoder(input_shape):\n",
    "    enc_inp, encoder = create_encoder(input_shape)\n",
    "    dec_inp, autoencoder = create_decoder(encoder)\n",
    "    model = Model(inputs=[enc_inp], outputs=[autoencoder], name='AutoEncoder')\n",
    "    \n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\OboTh\\Anaconda3\\envs\\lightweight-gpu-python\\lib\\site-packages\\tensorflow_core\\python\\ops\\resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "If using Keras pass *_constraint arguments to layers.\n",
      "WARNING:tensorflow:From C:\\Users\\OboTh\\Anaconda3\\envs\\lightweight-gpu-python\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:4070: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.\n",
      "\n",
      "Model: \"AutoEncoder\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         (None, 260, 540, 1)       0         \n",
      "_________________________________________________________________\n",
      "conv2d_1 (Conv2D)            (None, 260, 540, 64)      640       \n",
      "_________________________________________________________________\n",
      "batch_normalization_1 (Batch (None, 260, 540, 64)      256       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 130, 270, 64)      0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 130, 270, 32)      18464     \n",
      "_________________________________________________________________\n",
      "batch_normalization_2 (Batch (None, 130, 270, 32)      128       \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 130, 270, 32)      9248      \n",
      "_________________________________________________________________\n",
      "batch_normalization_3 (Batch (None, 130, 270, 32)      128       \n",
      "_________________________________________________________________\n",
      "up_sampling2d_1 (UpSampling2 (None, 260, 540, 32)      0         \n",
      "_________________________________________________________________\n",
      "conv2d_4 (Conv2D)            (None, 260, 540, 64)      18496     \n",
      "_________________________________________________________________\n",
      "batch_normalization_4 (Batch (None, 260, 540, 64)      256       \n",
      "_________________________________________________________________\n",
      "conv2d_5 (Conv2D)            (None, 260, 540, 1)       65        \n",
      "_________________________________________________________________\n",
      "batch_normalization_5 (Batch (None, 260, 540, 1)       4         \n",
      "=================================================================\n",
      "Total params: 47,685\n",
      "Trainable params: 47,299\n",
      "Non-trainable params: 386\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = create_autoencoder((height, width, 1))\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer='adam', loss='mse')\n",
    "epochs = 20\n",
    "batch_size = 8\n",
    "samples = len(x_train)\n",
    "validation_samples = len(x_valid)\n",
    "train_generator = model_train_generator(x_train, y_train, epochs=epochs, batch_size=batch_size, resize_shape=(height, width))\n",
    "valid_generator = model_valid_generator(x_valid, y_valid, epochs=epochs, resize_shape=(height, width))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train the AutoEncoder Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\OboTh\\Anaconda3\\envs\\lightweight-gpu-python\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:422: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
      "\n",
      "Epoch 1/20\n",
      "115/115 [==============================] - 49s 429ms/step - loss: 1.2062 - val_loss: 0.1817\n",
      "Epoch 2/20\n",
      "115/115 [==============================] - 43s 373ms/step - loss: 0.5792 - val_loss: 0.1720\n",
      "Epoch 3/20\n",
      "115/115 [==============================] - 43s 373ms/step - loss: 0.4297 - val_loss: 0.1399\n",
      "Epoch 4/20\n",
      "115/115 [==============================] - 43s 375ms/step - loss: 0.3160 - val_loss: 0.1023\n",
      "Epoch 5/20\n",
      "115/115 [==============================] - 44s 385ms/step - loss: 0.2276 - val_loss: 0.0609\n",
      "Epoch 6/20\n",
      "115/115 [==============================] - 44s 379ms/step - loss: 0.1599 - val_loss: 0.0292\n",
      "Epoch 7/20\n",
      "115/115 [==============================] - 43s 376ms/step - loss: 0.1091 - val_loss: 0.0112\n",
      "Epoch 8/20\n",
      "115/115 [==============================] - 43s 376ms/step - loss: 0.0730 - val_loss: 0.0074\n",
      "Epoch 9/20\n",
      "115/115 [==============================] - 44s 381ms/step - loss: 0.0473 - val_loss: 0.0055\n",
      "Epoch 10/20\n",
      "115/115 [==============================] - 45s 393ms/step - loss: 0.0301 - val_loss: 0.0047\n",
      "Epoch 11/20\n",
      "115/115 [==============================] - 45s 387ms/step - loss: 0.0189 - val_loss: 0.0041\n",
      "Epoch 12/20\n",
      "115/115 [==============================] - 43s 376ms/step - loss: 0.0118 - val_loss: 0.0042\n",
      "Epoch 13/20\n",
      "115/115 [==============================] - 44s 380ms/step - loss: 0.0075 - val_loss: 0.0061\n",
      "Epoch 14/20\n",
      "115/115 [==============================] - 43s 377ms/step - loss: 0.0051 - val_loss: 0.0048\n",
      "Epoch 15/20\n",
      "115/115 [==============================] - 43s 378ms/step - loss: 0.0037 - val_loss: 0.0045\n",
      "Epoch 16/20\n",
      "115/115 [==============================] - 43s 373ms/step - loss: 0.0029 - val_loss: 0.0045\n",
      "Epoch 17/20\n",
      "115/115 [==============================] - 44s 378ms/step - loss: 0.0025 - val_loss: 0.0048\n",
      "Epoch 18/20\n",
      "115/115 [==============================] - 43s 375ms/step - loss: 0.0023 - val_loss: 0.0047\n",
      "Epoch 19/20\n",
      "115/115 [==============================] - 43s 376ms/step - loss: 0.0022 - val_loss: 0.0043\n",
      "Epoch 20/20\n",
      "115/115 [==============================] - 44s 380ms/step - loss: 0.0021 - val_loss: 0.0042\n"
     ]
    }
   ],
   "source": [
    "hist_obj = model.fit_generator(train_generator, validation_data=valid_generator, validation_steps=validation_samples, steps_per_epoch=samples, epochs=epochs, shuffle=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x178605a27f0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist_pd = pd.DataFrame(hist_obj.history, index=np.arange(1, len(hist_obj.history['loss'])+1))\n",
    "hist_pd.index.name = 'epoch'\n",
    "sns.lineplot(data=hist_pd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_name = \"model.h5\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model = load_model(model_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_generator(x_test, resize_shape):\n",
    "    for sample in x_test:\n",
    "        img = cv2.imread(sample, cv2.IMREAD_GRAYSCALE) / 255.0\n",
    "        res_img = cv2.resize(img, resize_shape[::-1], interpolation=cv2.INTER_AREA)\n",
    "        res_img = np.expand_dims(res_img, 0)\n",
    "        res_img = np.expand_dims(res_img, 3)\n",
    "        np_img = np.array(res_img)\n",
    "        yield (np_img, np_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE Loss: 0.07084273546934128\n"
     ]
    }
   ],
   "source": [
    "steps = len(x_test)\n",
    "test_gen = test_generator(x_test, input_shape)\n",
    "loss = model.evaluate_generator(test_gen, steps=steps)\n",
    "print(\"MSE Loss:\", loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sample Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv2.imread(x_test[0], cv2.IMREAD_GRAYSCALE)\n",
    "img = cv2.resize(img, input_shape[::-1], interpolation=cv2.INTER_AREA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x17860bac2e8>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow(img, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_prediction(img):\n",
    "    processed = img / 255.0\n",
    "    processed = np.expand_dims(processed, 0)\n",
    "    processed = np.expand_dims(processed, 3)\n",
    "    pred = model.predict(processed)\n",
    "    pred = np.squeeze(pred, 3)\n",
    "    pred = np.squeeze(pred, 0)\n",
    "    out_img = pred * 255\n",
    "    out_img[out_img > 255.0] = 255.0\n",
    "    out_img = out_img.astype(np.uint8)\n",
    "    return out_img\n",
    "\n",
    "def path_leaf(path):\n",
    "    head, tail = ntpath.split(path)\n",
    "    return tail or ntpath.basename(head)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = make_prediction(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x17901eb3c50>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow(pred, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_dir = 'test_preds'\n",
    "if not os.path.exists(output_dir):\n",
    "    os.makedirs(output_dir)\n",
    "for x_test_file in x_test:\n",
    "    img = cv2.imread(x_test_file, cv2.IMREAD_GRAYSCALE)\n",
    "    img = cv2.resize(img, input_shape[::-1], interpolation=cv2.INTER_AREA)\n",
    "    pred = make_prediction(img)\n",
    "    filename = path_leaf(x_test_file)\n",
    "    filepath = os.path.join(output_dir, filename)\n",
    "    cv2.imwrite(filepath, pred)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "lightweight-gpu-kernel",
   "language": "python",
   "name": "lightweight-gpu-kernel"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
